Identifying computer servers that begin to behave differently than normal is a desirable action. But servers often inaccurately show out-of-variance metrics. This leads to an erroneous determination that a given server or set of servers are out of variance when they actually are not. These servers may exhibit a normal usage pattern, but it may be offset by an hour or some other timeframe. Or the accepted variance may be so small that almost any change, even a slight change, will result in a server being identified on a variance report (albeit inaccurately). The result is that many of the servers on the variance report should not be present, and much time is wasted by unnecessarily analyzing servers that never really needed to be analyzed.
Ultimately, those people who should normally rely on the accuracy of variance reports end up discounting their value or not relying on them at all. If a variance report is dominated by servers that are not really exhibiting variant traits, and thus are likely working properly, then relevant personnel will tend to dismiss the reports, and the gains sought to be offered by such a report will not only not be realized, but will actually create a worse situation than not having a report because resources were expended to make something that is not used.
The current state of the art could be improved by providing, among other things, a method to determine meaningful and accurate server variance (including variances that are an aberration when compared to past data), which can then be used to accurately identify when a server may be reaching capacity or suffering from some other ailment.